At this point, it would be useful to consolidate our code. We have written a lot of code so far, including helper functions. Let's consolidate the helper functions into a utils.py file as follows.

First, we import the necessary libraries:

import numpy as np
import random
import os
import cv2
from keras.models import Sequential
from keras.layers import Flatten, Dense, Conv2D, MaxPooling2D
from keras import backend as K
from keras.preprocessing.image import load_img, img_to_array

We include the euclidean_distance, contrastive_loss, and accuracy functions needed to train a Siamese neural network in the utils.py file:

def euclidean_distance(vectors):
    vector1, vector2 = vectors
    sum_square = K.sum(K.square(vector1 - vector2), axis=1, keepdims=True)
    return K.sqrt(K.maximum(sum_square, K.epsilon()))

def contrastive_loss(Y_true, D):
    margin = 1
    return...